How do cyclists make their way? - A GPS-based revealed preference study in Copenhagen

Abstract

It is the objective of the study to determine the extent to which human navigation is affected by perceptions of our immediate surroundings or by already established knowledge in terms of a cognitive map. The motivation is to contribute to the knowledge about human navigation and to inform planning with estimates of bicyclists' route preferences and 'willingness-to-pay' (in terms of transport distance vs utility/disutility of route characteristics). The core method is choice modelling of observed route data. 1,267 trips performed by 183 cyclists in Copenhagen (Denmark) were recorded by GPS. The trips were map-matched to a digital road and path network, which enabled the generation of choice sets: one for navigation as influenced by perception of immediate surroundings, comprising edges connected to network-nodes (hereafter called the edge dataset), and one for navigation based on a priori knowledge, comprising the trip itself and a number of alternative routes generated by a labelling algorithm (hereafter called the route dataset). The results document that choices based on characteristics of both the route and the edge data can be estimated and provide reasonable and significant parameter estimates regarding cyclists' preferences. Length was significant and negative, illustrating that cyclistseverything else kept equalprefer to bike shorter distances. Preferences regarding characteristics of bike path, presence of traffic lights and road types show similar results to the two types of data; most importantly that routes with facilities, such as curbed tracks and segregated bikeways, were significantly preferred. The study concludes that cyclists' wayfinding can be modelled as choices based on both an edge dataset and a route dataset and, thus, may be influenced by both perceived information and a priori knowledge. We suggest that future analyses of movement and route preferences take both modes into account as actual movement may be based on a combination of the two and because assessment of the influence of the immediate, perceivable surroundings can provide information not to be considered in a wayfinding approach. In our case differences in preferences along the route is for example found, but this can be expanded in future studies to also include dynamic aspects such as weather and crowding.

Fear Factor: Level of Traffic Stress and GPS Assessed Cycling Routes

“…The difference in distance between actual and shortest routes in this study was greater than reported by others [40] [57] [58] [59], however was not statistically significant. Findings lend support to previous studies that have shown cyclists prefer to travel on lower stress roads, but also value directness [25] [40] [58] [60]. In our sample, cyclists may have chosen slightly longer routes in order to travel on lower stress roads, but were unwilling to travel the excessive distances required to travel on exclusively low stress routes, if available.…”

Kentsel Alanda CBS Kullanarak Bisiklet Altyapısı Rota Planlaması: İzmir Örneği

“…Studies about how to determine bicycle routes in cities emerge in various fields (e.g., urban geography, transportation, urban planning and urban design) and pay attention on the concerns about health and physical activity, healthy living, sustainable transportation and non-motorized transportation (e.g., Saelens et al 2003, Huang and Ye 1995, Wendel-Vos et al 2004, Segadilha and da Penha Sanches 2014, Blečić et al 2015. Deploying GIS tools, the researchers about bicycle network planning emphasize the route choice criteria for bicycling in relation to the physical, infrastructural and natural characteristics of settlements (e.g., Rybarczyk and Wu 2010) and to the modelling of bicyclists' route preferences by GPS records as well as to cycling demand of population in terms of transport distance and quality of route utilities (e.g, Skov-Petersen et al 2018).…”

Organizing bicycle traffic in Moscow to reduce air pollutant concentrations

“…Despite the fact that E3S Web of Conferences 164, 04007 (2020) TPACEE-2019 https://doi.org/10.1051/e3sconf /202016404007 every second resident of Copenhagen owns a car, over fifty percent of urban residents use bicycles to travel around the city. The share of residents that travel around the city by cars, has plummeted to 24% [12]. It is assumed that the cycling transport development produces impact on communications between residents of the Danish capital [13].…”